Searching for Connections between Teacher Program Applicant Information and Selection, and STEM Teacher Retention and Effectiveness to Inform Teacher Recruitment and Education

该项目旨在满足国家对高素质科学、技术、工程和数学（STEM）教师的需求。为此，它将寻找潜在教师候选人的信息之间的联系，例如考试成绩和STEM成绩；STEM教师教育项目的准入和注册；以及他们后来作为STEM教师的留任率和效率。人们对提高美国STEM教师队伍的质量有着浓厚的兴趣。然而，令人惊讶的是，关于教师教育项目应用中的信息是否能预测STEM教师的留任和有效性，人们知之甚少。本研究旨在提供有关教师教育项目录取的经验证据，这是影响美国STEM教师队伍质量的关键第一步。具体要调查的研究问题包括：1。特定类型的申请人信息是否可以预测STEM教师的留任？2. 申请人信息是否可以预测STEM教师的有效性？3. 申请人的信息在有效性分布上对保留率有不同的预测吗？4. 申请人信息对高需求教育机构的保留率和有效性有不同的预测吗？这些问题的答案可能会揭示申请人信息和教师成果之间的联系。这些信息可以为STEM教师教育项目的招聘和录取决策提供信息。因此，该项目有可能改善国家的整体战略，以确保高质量的STEM教师队伍。该项目是美国研究院教育研究纵向数据分析中心、华盛顿州教育研究和数据中心以及培养STEM教师的五所华盛顿州大学（中央华盛顿大学、太平洋路德大学、华盛顿大学、华盛顿州立大学和西华盛顿大学）之间的合作项目。这项研究是通过华盛顿州学生和教师的全州数据来实现的，这些数据包括：1)来自该州所有高需求教育机构的数据；2)州内公立高校STEM教师候选人的大学成绩单数据；3)五所合作大学的招生过程和招生数据。这些定量数据的来源将被结合起来，以允许基于回归的分析大学申请者的属性，这些属性与STEM教师的有效性和保留相关。该项目还将从合作大学的教师那里收集定性数据，以更好地了解STEM教师教育项目的教师对潜在教师候选人的重视程度，以及他们的重视程度是否与参与大学的录取和招生有关。该项目以经济和社会文化理论为依据。经济理论基础将教师教育项目的运作置于公共劳动力市场中，在这个市场中，申请人的信息是由决策者的背景、经验和社会背景过滤的。鉴于这项工作的潜在相关性的广度，项目结果不仅将通过学术期刊传播，还将通过国家和州会议、项目网站以及与州各地利益相关者的项目会议传播。本Track 4: Noyce研究项目由Robert Noyce教师奖学金计划（Noyce）支持。Noyce计划支持有才华的STEM本科专业和专业人士成为有效的K-12 STEM教师，并支持经验丰富的模范K-12 STEM教师成为高需求学区的STEM硕士教师。它还支持对高需求学区K-12 STEM教师的持久性、留任性和有效性的研究。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This project aims to serve the national need for high-quality science, technology, engineering, and math (STEM) teachers. To do so, it will look for connections between information from potential teacher candidates, such as test scores and STEM grades; their admittance to and enrollment in STEM teacher education programs; and their later retention and effectiveness as STEM teachers. There is intense interest in improving the quality of the U.S. STEM teacher workforce. However, surprisingly little is known about whether information in applications to teacher education programs predict or do not predict STEM teacher retention and effectiveness. This study is designed to generate empirical evidence about admissions into teacher education programs, the crucial first step to influencing the quality of the nation’s STEM teacher workforce. The specific research questions to be investigated include: 1. Are specific types of applicant information predictive of STEM teacher retention? 2. Is applicant information predictive of STEM teacher effectiveness? 3. Is applicant information differentially predictive of retention along the effectiveness distribution? 4. Is applicant information differentially predictive of retention and effectiveness in high-need educational agencies? Answers to these questions may reveal connections between applicant information and teacher outcomes. Such information could inform decisions about recruitment and admissions into STEM teacher education programs. As a result, the project has the potential to improve the nation’s overall strategy for ensuring a high-quality STEM teacher workforce. This project is a collaboration between the Center for Analysis of Longitudinal Data in Education Research at the American Institutes for Research, Washington State’s Education Research and Data Center and five Washington State universities that prepare STEM teachers (Central Washington University, Pacific Lutheran University, University of Washington, Washington State University, and Western Washington University). This research study is made possible by statewide data about students and teachers in Washington that include: 1) data from all high-need educational agencies in the state; 2) college transcript data about STEM teacher candidates enrolled in public colleges and universities in the state; and 3) data about admissions processes and admissions from the five collaborating Universities. These sources of quantitative data will be combined to permit regression-based analyses of the attributes of college applicants that are correlated with STEM teacher effectiveness and retention. The project will also collect qualitative data from faculty at collaborating universities to better understand what faculty in STEM teacher education programs value in prospective teacher candidates and whether what they value is related to admission and enrollment in the participating universities. The project is informed by economical and socio-cultural theories. The economical theoretical basis places teacher education program operations within a public labor market in which applicant information is filtered by decision makers’ backgrounds, experiences, and social contexts. Given the breadth of potential relevance of this work, project results will be disseminated not only through academic journals, but also through national and state conferences, project websites, and a project conference with stakeholders from around the state. This Track 4: Noyce Research project is supported through the Robert Noyce Teacher Scholarship Program (Noyce). The Noyce program supports talented STEM undergraduate majors and professionals to become effective K-12 STEM teachers and experienced, exemplary K-12 STEM teachers to become STEM master teachers in high-need school districts. It also supports research on the persistence, retention, and effectiveness of K-12 STEM teachers in high-need school districts.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.